A Comparative Study of Machine Learning Algorithms for Diagnosis of Ischemic Heart Disease

Pyoung-Woo Park, Min-Koo Kim, Hong-Seok Lim, Duk-Yong Yoon, Seok-Won Lee

http://doi.org/10.5626/JOK.2018.45.4.376

In recent years, studies on artificial intelligence have been actively conducted, and artificial intelligence technology supports accurate and efficient decision-making for mankind. Also, the accumulation of medical knowledge and related data is accelerating, and studies on diagnosis of diseases through artificial intelligence technology are being carried out briskly. In this study, I chose a representative cardiovascular disease, specifically ischemic heart disease, as a research domain, and analyzed the available algorithms comparing effective approaches in the medical expert system for diagnosis of the disease. Concretely, the purpose of the study is to assist medical experts and physicians based on the initial patient record data, help them to explain the cause of ischemic heart disease, and minimize unnecessary related tests. In addition, the experimental data can be configured so that medical professionals can use them as learning models, thereby maximizing their experience and knowledge efficiently.